I’m currently an associate professor in the School of Computer Science and Engineering at Beihang University (BUAA). Before that, I received my Ph.D. degree from Beihang University, under the supervision of Prof. Jianxin Li. Further before, I obtained the B.S. degree from Xidian University.

My research interests include Deep Graph Learning, Agent and Trustworthy AI. Please feel free to send me an email if interested to discuss or work together.

[Prospective students] Our group has positions for Ph.D. students, Master students, and visiting students. If you are interested, please send me an email with your CV and publications (if any).

🔥 News

• 2026.09  🌟 We will give a tutorial GraphMedIA: Graph Learning in Medical Image Analysis at MICCAI 2026. See you in Strasbourg!

• 2026.08  🎉 One paper is accepted by ICDM 2026

• 2026.08  🎉 Two papers are accepted by CIKM 2026

• 2026.07  🎉 Our survey on Foundation Models for Structured Data paper is accepted by IEEE TKDE

• 2026.07 🎉 Two papers are accepted by MM 2026

• 2026.06  🌟 We are organizing a Foundation Models and Agentic Intelligence for Graph-Centric Applications special issue for the TGINA. Welcome submissions!

• 2026.05  🎉 Two papers are accepted by ICML 2026

• 2026.02  🌟 We will organize the 2nd Workshop on Frontiers in Graph Machine Learning for the Large Model Era in KDD 2026. See you in Jeju!

• 2026.01  🎉 One paper is accepted by ICLR 2026

• 2026.01  🌟 I will give a invited talk in 5th Workshop on Graphs and more Complex Structures For Learning and Reasoning in AAAI 2026. See you in Singapore!

• 2026.01  🎉 Five papers are accepted by WWW 2026

• 2025.11  🎉 One paper is accepted by KDD 2026

• 2025.11  🎉 Six papers are accepted by AAAI 2026

• 2025.10  🎉 One paper is accepted by IEEE TPAMI

• 2025.10  🎉 One paper is accepted by IEEE SMC

• 2025.09  🎉 Four papers are accepted by NeurIPS 2025

• 2025.07  🌟 We will organize a workshop regarding Frontiers in Graph Machine Learning for the Large Model Era in CIKM 2025. See you in Seoul!

• 2025.06  🎉 One paper is accepted by IEEE TKDE

• 2025.05  🌟 We will give a tutorial regarding Towards Low-Distortion Graph Representation Learning at IJCAI 2025. See you in Guangzhou!

• 2025.05  🌟 We host a challenge Characterizing User Behavior in Social Networks: Propagation, Prediction, and Sensemaking at IJCAI 2025. Welcome to join!

• 2025.05  🎉 One paper is accepted by ACL 2025

• 2025.05  🎉 One paper is accepted by ICML 2025

• 2025.04  🎉 Three papers are accepted by IJCAI 2025

• 2025.01  🎉 Two papers are accepted by ICLR 2025

• 2025.01  🎉 One paper is accepted by WWW 2025

📝 Publications

* denotes equal contribution and # denotes corresponding author

2026:

• Preprint Information-Theoretic Foundations and Advances in Graph Machine Learning: A Comprehensive Survey. Qingyun Sun, Yi Huang, Haonan Yuan, Xingcheng Fu, Yisen Gao, Jia Wu, Shujian Yu, Angsheng Li, Jianxin Li, Philip S Yu

• Preprint CRITIC-R1: Learning Structured Critics for Retrieval-Augmented Generation. Wenhan Xiao, Ziwei Zhang, Chuanyue Yu, Xingcheng Fu, Qingyun Sun, Runhua Xu, Jianxin Li

• Preprint DyG-RAG: Dynamic Graph Retrieval-Augmented Generation with Event-Centric Reasoning. Qingyun Sun, Jiaqi Yuan, Shan He, Xiao Guan, Haonan Yuan, Xingcheng Fu, Jianxin Li, Philip S Yu

• Preprint AgenticGEO: A Self-Evolving Agentic System for Generative Engine Optimization. Jiaqi Yuan, Jialu Wang, Zihan Wang, Qingyun Sun, Ruijie Wang, Jianxin Li

• Preprint Unlocking the Potentials of Retrieval-Augmented Generation for Diffusion Language Models. Chuanyue Yu, Jiahui Wang, Yuhan Li, Heng Chang, Ge Lan, Qingyun Sun, Jia Li, Jianxin Li, Ziwei Zhang

• Preprint Future Forcing: Future-aware Training-free KV Cache Policy for Autoregressive Video Generation. Jiayi Luo, Qiyan Liu, Tengyang Wang, JunHao Liu, Jiayu Chen, Cong Wang, Hanxin Zhu, Chen Gao, Xiaobin Hu, Qingyun Sun, Zhibo Chen

• IEEE TKDE 2026 A Survey on Foundation Models for Structured Data: Tabular, Time Series, and Graphs. Qingyun Sun, Haonan Yuan, Yi Huang, Ziwei Zhang, Xingcheng Fu, Ruijie Wang, Haoyi Zhou, Jianxin Li, Jia Wu, Philip S. Yu

• MM 2026 DualG-MRAG: Decoupling Macro-Reasoning and Micro-Matching for Multimodal Retrieval-Augmented Generation. Jiacheng Tao, Qingyun Sun#, Haonan Yuan, Ziwei Zhang, Jianxin Li

• MM 2026 So-Called Input Transformation-Based Attacks Are Actually Model Transformation-Based Attacks. Yang Hu, Tao Yang, Yuheng He, Qingyun Sun, Xiuli Bi, Bin Xiao, Jianxin Li

• ICML 2026 Is Fixing Schema Graphs Necessary? Full-Resolution Graph Structure Learning for Relational Deep Learning. Yi Huang, Qingyun Sun#, Jia Li, Xingcheng Fu, Jianxin Li

• ICML 2026 Training-Free Sparse Attention for Fast Video Generation via Offline Layer-Wise Sparsity Profiling and Online Bidirectional Co-Clustering. Jiayi Luo, Jiayu Chen, Jiankun Wang, Cong Wang, Hanxin Zhu, Qingyun Sun, Chen Gao, Zhibo Chen, Jianxin Li

• ICLR 2026 Controllable Logical Hypothesis Generation for Abductive Reasoning in Knowledge Graphs. Yisen Gao, Jiaxin Bai, Tianshi Zheng, Ziwei Zhang, Qingyun Sun, Xingcheng Fu, Jianxin Li, Yangqiu Song

• WWW 2026 Graph Diffusion Evolution Model for Multi-Conditional Molecular Generation. Xingcheng Fu, Lingyun Liu, Yisen Gao, Tianyu Chen, Qingyun Sun#, Jianxin Li, Xianxian Li

• WWW 2026 Overcoming In-Memory Bottlenecks in Graph Foundation Models via Retrieval-Augmented Generation. Haonan Yuan, Qingyun Sun, Jiacheng Tao, Xingcheng Fu, Jianxin Li

• WWW 2026 Towards Geometry-Consistent Federated Graph Learning. Yuecen Wei, Zhiyu Zhuang, Yisen Gao, Xingcheng Fu, Qingyun Sun, Ziwei Zhang, Tianyu Wo, Chunming Hu

• WWW 2026 GraphRAG-R1: Graph Retrieval-Augmented Generation with Process-Constrained Reinforcement Learning. Chuanyue Yu, Kuo Zhao, Yuhan Li, Heng Chang, Mingjian Feng, Xiangzhe Jiang, Yufei Sun, Jia Li, Yuzhi Zhang, Qingyun Sun, Jianxin Li, Ziwei Zhang

• WWW 2026 Unifying Deductive and Abductive Reasoning in Knowledge Graphs with Masked Diffusion Model. Yisen Gao, Jiaxin Bai, Yi Huang, Xingcheng Fu, Qingyun Sun, Yangqiu Song

• KDD 2026 Mitigating Privacy Risks in Graph Condensation from a Hyperbolic Geometry Perspective. Yuecen Wei, Liu Yang, Beining Yang, Qingyun Sun, Hao Peng, Tianyu Wo, Chunming Hu, Xingcheng Fu

• AAAI 2026(Oral) Is the Information Bottleneck Robust Enough? Towards Label-Noise Resistant Information Bottleneck Learning. Yi Huang, Qingyun Sun#, Yisen Gao, Haonan Yuan, Xingcheng Fu, Jianxin Li

• AAAI 2026 SA²GFM: Enhancing Robust Graph Foundation Models with Structure-Aware Semantic Augmentation. Junhua Shi, Qingyun Sun#, Haonan Yuan, Xingcheng Fu

• AAAI 2026(Oral) Privacy Auditing of Multi-domain Graph Pre-trained Model under Membership Inference Attacks. Jiayi Luo, Qingyun Sun, Yuecen Wei, Haonan Yuan, Xingcheng Fu, Jianxin Li

• AAAI 2026 Towards Effective, Stealthy, and Persistent Backdoor Attacks Targeting Graph Foundation Models. Jiayi Luo, Qingyun Sun, Lingjuan Lyu, Ziwei Zhang, Haonan Yuan, Xingcheng Fu, Jianxin Li

• AAAI 2026 Fine-Tuned LLMs Know They Don’t Know: A Parameter-Efficient Approach to Recovering Honesty. Zeyu Shi, Ziming Wang, Haoyi Zhou, Shiqi Gao, Tianyu Chen, Qingyun Sun, Jianxin Li

• AAAI 2026 Towards LLM-Empowered Knowledge Tracing via LLM-Student Hierarchical Behavior Alignment in Hyperbolic Space. Xingcheng Fu, Shengpeng Wang, Yisen Gao, Dongran Yu, Chunpei Li, Qingyun Sun, Xianxian Li

• CIKM 2026 Rich-Media Re-Ranker: A User Satisfaction-Driven LLM Re-ranking Framework for Rich-Media Search. Zihao Guo, Ligang Zhou#, Zeyang Tang, Feicheng Li, Ying Nie, Zhiming Peng, Qingyun Sun#, Jianxin Li

• ICDM 2026 Zero-shot Generalizable Graph Anomaly Detection with Mixture of Riemannian Experts. Xinyu Zhao, Qingyun Sun#, Jiayi Luo, Xingcheng Fu, Jianxin Li

2025:

• IEEE TPAMI 2025 Evolving Graph Learning for Out-of-Distribution Generalization in Non-stationary Environments. Qingyun Sun, Jiayi Luo, Haonan Yuan, Xingcheng Fu, Hao Peng, Jianxin Li, Philip S. Yu

• IEEE SMC Precise influence evaluation in complex networks. Bingyu Zhu, Qingyun Sun, Jianxin Li, Daqing Li

• NeurIPS 2025(Spotlight) Robust Graph Condensation via Classification Complexity Mitigation. Jiayi Luo, Qingyun Sun, Beining Yang, Haonan Yuan, Xingcheng Fu, Yanbiao Ma, Jianxin Li, Philip S. Yu

• NeurIPS 2025 GRAVER: Generative Graph Vocabularies for Robust Graph Foundation Models Fine-tuning. Haonan Yuan, Qingyun Sun#, Junhua Shi, Xingcheng Fu, Bryan Hooi, Jianxin Li, Philip S. Yu

• NeurIPS 2025 GraphKeeper: Graph Domain-Incremental Learning via Knowledge Disentanglement and Preservation. Zihao Guo, Qingyun Sun#, Ziwei Zhang, Haonan Yuan, Huiping Zhuang, Xingcheng Fu, Jianxin Li

• NeurIPS 2025 Toward a Unified Geometry Understanding: Riemannian Diffusion Framework for Graph Generation and Prediction. Yisen Gao, Xingcheng Fu, Qingyun Sun, Jianxin Li, Xianxian Li

• ICML 2025 How Much Can Transfer? BRIDGE: Bounded Multi-Domain Graph Foundation Model with Generalization Guarantees. Haonan Yuan, Qingyun Sun#, Junhua Shi, Xingcheng Fu, Bryan Hooi, Jianxin Li, Philip S. Yu

• IEEE TKDE 2025 Hierarchical Text Classification Optimization via Structural Entropy and Singular Smoothing. Qitong Liu, Hao Peng, Xiang Huang, Zhifeng Hao, Qingyun Sun, Zhengtao Yu, Philip S Yu

• ICLR 2025 (Spotlight) IGL-Bench: Establishing the Comprehensive Benchmark for Imbalanced Graph Learning. Jiawen Qin*, Haonan Yuan*, Qingyun Sun*, Lyujin Xu, Jiaqi Yuan, Pengfeng Huang, Zhaonan Wang, Xingcheng Fu, Hao Peng, Jianxin Li, Philip S. Yu

• ICLR 2025 ST-GCond: Self-supervised and Transferable Graph Dataset Condensation. Beining Yang, Qingyun Sun#, Cheng Ji, Xingcheng Fu, Jianxin Li

• ACL 2025 Towards Objective Fine-tuning: How LLMs’ Prior Knowledge Causes Potential Poor Calibration? Ziming Wang, Zeyu Shi, Haoyi Zhou, Shiqi Gao, Qingyun Sun, Jianxin Li

• IJCAI 2025 OS-GCL: A One-Shot Learner in Graph Contrastive Learning. Cheng Ji, Chenrui He, Qian Li, Qingyun Sun, Xingcheng Fu, Jianxin Li

• IJCAI 2025 Mitigating Message Imbalance in Fraud Detection with Dual-View Graph Representation Learning. Yudan Song, Yuecen Wei, Yuhang Lu, Qingyun Sun, Xingcheng Fu, Minglai Shao, Li-e Wang, Chunming Hu, Xianxian Li

• IJCAI 2025 An Out-Of-Distribution Membership Inference Attack Approach for Cross-Domain Graph Attacks. Jinyan Wang, Liu Yang, Yuecen Wei, Jiaxuan Si, Chenhao Guo, Qingyun Sun, Xingcheng Fu, Xianxian Li

• WWW 2025 Robust Graph Learning Against Adversarial Evasion Attacks via Prior-Free Diffusion-Based Structure Purification. Jiayi Luo, Qingyun Sun#, Haonan Yuan, Xingcheng Fu, Jianxin Li

• AAAI 2025 GraphMoRE: Mitigating Topological Heterogeneity via Mixture of Riemannian Experts. Zihao Guo, Qingyun Sun#, Haonan Yuan, Xingcheng Fu, Min Zhou, Yisen Gao, Jianxin Li

• AAAI 2025 DG-Mamba: Robust and Efficient Dynamic Graph Structure Learning with Selective State Space Models. Haonan Yuan, Qingyun Sun, Zhaonan Wang, Xingcheng Fu, Cheng Ji, Yongjian Wang, Bo Jin, Jianxin Li

• AAAI 2025 Discrete Curvature Graph Information Bottleneck. Xingcheng Fu#, Jian Wang, Yisen Gao, Qingyun Sun#, Haonan Yuan, Jianxin Li, Xianxian Li

• AAAI 2025 Bi-Directional Multi-Scale Graph Dataset Condensation via Information Bottleneck. Xingcheng Fu, Yisen Gao, Beining Yang, Yuxuan Wu, Haodong Qian, Qingyun Sun, Xianxian Li

• AAAI 2025 Prompt-based Unifying Inference Attack on Graph Neural Networks. Yuecen Wei, Xingcheng Fu, Lingyun Liu, Qingyun Sun, Hao Peng, Chunming Hu

• WSDM 2025 Graph Size-imbalanced Learning with Energy-guided Structural Smoothing. Jiawen Qin, Pengfeng Huang, Qingyun Sun, Cheng Ji, Xingcheng Fu, Jianxin Li

• NN 2025 Augmenting sparse behavior data for user identity linkage with self-generated by model and mixup-generated samples. Hongren Huang, Jianxin Li, Feihong Lu, Lihong Wang, Qian Li, Qingyun Sun

• JMLC 2025 A comprehensive survey on GNN-based anomaly detection: taxonomy, methods, and the role of large language models. Ziqi Yuan, Qingyun Sun#, Haoyi Zhou, Minglai Shao, Xingcheng Fu

2024:

• NeurIPS 2024 GC-Bench: An Open and Unified Benchmark for Graph Condensation. Qingyun Sun*, Ziying Chen*, Beining Yang, Cheng Ji, Xingcheng Fu, Sheng Zhou, Hao Peng, Jianxin Li, Philip S. Yu

• SCIS 2024 Hierarchical graph structure learning with nonlinear information bottleneck. Qingyun Sun, Jiayi Luo, Beining Yang, Jianxin Li

• WWW 2024 Dynamic Graph Information Bottleneck. Haonan Yuan, Qingyun Sun#, Xingcheng Fu, Cheng Ji, Jianxin Li

• ICML 2024 Hyperbolic Geometric Latent Diffusion Model for Graph Generation. Xingcheng Fu, Yisen Gao, Yuecen Wei, Qingyun Sun, Hao Peng, Jianxin Li, Xianxian Li

• MM 2024 MIKO: Multimodal Intention Knowledge Distillation from Large Language Models for Social-Media Commonsense Discovery. Feihong Lu, Weiqi Wang, Yangyifei Luo, Ziqin Zhu, Qingyun Sun#, Baixuan Xu, Haochen Shi, Shiqi Gao, Qian Li, Yangqiu Song, Jianxin Li

• AAAI 2024 ReGCL: Rethinking Message Passing in Graph Contrastive Learning. Cheng Ji, Zixuan Huang, Qingyun Sun, Hao Peng, Xingcheng Fu, Qian Li, Jianxin Li

• AAAI 2024 Poincar’e Differentially Private for Hierarchy-aware Graph Emebedding. Yuecen Wei, Haonan Yuan, Xingcheng Fu, Qingyun Sun, Hao Peng, Xianxian Li, Chunming Hu

• SDM 2024 MultiNetAD: Multiplex Network-Based Anomaly Access Detection Featuring Semantic Hierarchies. Ziqi Yuan, Qingyun Sun, Haoyi Zhou, Zukun Zhu, Jianxin Li

• COLING 2024 Few-Shot Multimodal Named Entity Recognition based on Mutlimodal Causal Intervention Graph. Feihong Lu, Xiaocui Yang, Qian Li, Qingyun Sun#, Ke Jiang,Cheng Ji, Jianxin Li

• CIKM 2024 L-APPLE: Language-agnostic Prototype Prefix Learning for Cross-lingual Event Detection. Ziqin Zhu, Xutan Peng, Qian Li, Cheng Ji, Qingyun Sun, Jianxin Li

• IJCAI 2024 GAAMAL Beyond Human Preferences: Exploring Reinforcement Learning Trajectory Evaluation and Improvement through LLMs. Zichao Shen, Tianchen Zhu, Qingyun Sun#, Shiqi Gao, Jianxin Li

• Preprint Motif-driven Subgraph Structure Learning for Graph Classification. Zhiyao Zhou, Sheng Zhou, Bochao Mao, Jiawei Chen, Qingyun Sun, Yan Feng, Chun Chen, Can Wang

2023:

• IEEE TPAMI 2023 Adaptive Subgraph Neural Network with Reinforced Critical Structure Mining. Jianxin Li, Qingyun Sun, Hao Peng, Beining Yang, Jia Wu, Phillp S. Yu

• AAAI 2023 Self-organization Preserved Graph Structure Learning with Principle of Relevant Information. Qingyun Sun, Jianxin Li, Beining Yang, Xingcheng Fu, Hao Peng, Philip S. Yu

• NeurIPS 2023 Environment-Aware Dynamic Graph Learning for Out-of-Distribution Generalization. Haonan Yuan, Qingyun Sun#, Xingcheng Fu, Ziwei Zhang, Cheng Ji, Hao Peng, Jianxin Li

• NeurIPS 2023 Does Graph Distillation See Like Vision Dataset Counterpart?. Beining Yang, Kai Wang, Qingyun Sun, Cheng Ji, Xingcheng Fu, Hao Tang, Yang You, Jianxin Li

• WWW 2023 (Spotlight Paper) Hyperbolic Geometric Graph Representation Learning for Hierarchy-imbalance Node Classification. Xingcheng Fu, Yuecen Wei, Qingyun Sun, Haonan Yuan, Jia Wu, Hao Peng, Jianxin Li

• IEEE TKDE 2023 A Robust and Generalized Framework for Adversarial Graph Embedding. Jianxin Li, Xingcheng Fu, Hao Peng, Senzhang Wang, Shijie Zhu, Qingyun Sun, Philip S. Yu, Lifang He

• PR 2023 Higher-Order Memory Guided Temporal Random Walk for Dynamic Heterogeneous Network Embedding. Cheng Ji, Tao Zhao, Qingyun Sun, Xingcheng Fu, Jianxin Li

• WSDM 2023 Unbiased and Efficient Self-Supervised Incremental Contrastive Learning. Cheng Ji, Jianxin Li, Hao Peng, Jia Wu, Xingcheng Fu, Qingyun Sun, Philip S. Yu

• KAIS 2023 Adaptive Curvature Exploration Geometric Graph Neural Network. Xingcheng Fu, Jianxin Li, Jia Wu, Jiawen Qin, Qingyun Sun, Cheng Ji, Senzhang Wang, Hao Peng, Philip S. Yu

• KAIS 2023 Heterogeneous Graph Neural Network with Semantic-aware Differential Privacy Guarantees. Yuecen Wei, Xingcheng Fu, Dongqi Yan, Qingyun Sun, Hao Peng, Jia Wu, Jinyan Wang, Xianxian Li

Before 2022:

• AAAI 2022 Graph Structure Learning with Variational Information Bottleneck. Qingyun Sun, Jianxin Li, Hao Peng, Jia Wu, Xingcheng Fu, Cheng Ji, Philip S. Yu

• WWW 2022 Curvature Graph Generative Adversarial Networks. Jianxin Li, Xingcheng Fu, Qingyun Sun, Cheng Ji, Jiajun Tan, Jia Wu, Hao Peng

• CIKM 2022 (Best Paper Honorable Mention Award) Position-aware Structure Learning for Graph Topology-imbalance by Relieving Under-reaching and Over-squashing. Qingyun Sun, Jianxin Li, Haonan Yuan, Xingcheng Fu, Hao Peng, Cheng Ji, Qian Li, Philip S. Yu

• CIKM 2022 Automating DBSCAN via Deep Reinforcement Learning. Ruitong Zhang, Hao Peng, Yingtong Dou, Jia Wu, Qingyun Sun, Yangyang Li, Jingyi Zhang, Philip S. Yu

• IWQoS 2022 (Best Paper Award) AIQoSer: Building the efficient Inference-QoS for AI Services. Jianxin Li, Tianchen Zhu, Haoyi Zhou, Qingyun Sun, Chunyang Jiang, Shuai Zhang, Chunming Hu

• ICDM 2022 Heterogeneous Graph Neural Network for Privacy-Preserving Recommendation. Yuecen Wei, Xingcheng Fu, Qingyun Sun, Hao Peng, Jia Wu, Jinyan Wang, Xianxian Li

• ACM TWEB 2022 Type Information Utilized Event Detection via Multi-Channel GNNs in Electrical Power Systems. Qian Li, Jianxin Li, Lihong Wang, Cheng Ji, Yiming Hei, Jiawei Sheng, Qingyun Sun, Shan Xue, Pengtao Xie

• WWW 2021 (Most Influential WWW Papers) SUGAR: Subgraph Neural Network with Reinforcement Pooling and Self-Supervised Mutual Information Mechanism. Qingyun Sun, Jianxin Li, Hao Peng, Jia Wu, Yuanxing Ning, Philip S. Yu, Lifang He

• ICDM 2021 (Best Paper Candidate) ACE-HGNN: Adaptive Curvature Exploration Hyperbolic Graph Neural Network. Xingcheng Fu, Jianxin Li, Jia Wu, Qingyun Sun, Cheng Ji, Senzhang Wang, Jiajun Tan, Hao Peng, Philip S. Yu

• ICDM 2020 Pairwise Learning for Name Disambiguation in Large-Scale Heterogeneous Academic Networks. Qingyun Sun*, Hao Peng*, Jianxin Li, Senzhang Wang, Xiangyu Dong, Liangxuan Zhao, Philip S. Yu, Lifang He

🏆 Honors and Awards

• 2025.11 Chinese Institute of Electronics (CIE) Young Elite Scientists Sponsorship Program

• 2025.03 Chinese Institute of Electronics (CIE) Outstanding Doctoral Dissertation Award

• 2024.08  CCF Bigdata 2024 Best Paper Award

• 2024.04  Most Popular Speaker of the Year” at the Techbeat.net

• 2023.12  Excellence Award in Pretrained Model-based Community Detection and Fraudulent Group Mining Competition @ICDM 2023

• 2023.09  2023 ACM China Beijing Doctoral Dissertation Award

• 2022.10  CIKM 2022 Best Paper Honorable Mention Award

• 2022.07  Huawei Scholarship

• 2022.10  IEEE IWQoS 2022 Best Paper Award

• 2022.06  The First Prize of 2022 CCF Academic Show (Ph.D. Group)

• 2021.10  ICDM 2021 Best Paper Candidate

• 2021.03  Student Scholarship Award of The Web Conference 2021

💬 Invited Talks

• 2026.09 MICCAI 2026, Tutorial: GraphMedIA: Graph Learning in Medical Image Analysis

• 2026.01  AAAI 2026: 5th Workshop on Graphs and more Complex Structures For Learning and Reasoning, Graph Machine Learning for the Large Model Era.

• 2025.11  AI TIME, NeuIPS 2026 Pre-talk ACT-BD session. [video]

• 2025.09  CCF Bigdata 2025, Graph Structure Learning for Knowledge in Big Data.

• 2025.08  IJCAI 2025, Tutorial: Towards Low-Distortion Graph Representation Learning.

• 2025.01  AI TIME, AAAI 2025 Pre-talk ACT-BD session. [video]

• 2024.12  LOG 2024 Kunshan Meetup, Towards Low-Distortion Graph Representation Learning.

• 2024.12  CCF Intelligence Transportation Systems Conference 2024, Research and Application of Graph Structure Learning and Long-Sequence Prediction.

• 2024.08  CCF Bigdata 2024, Graph Learning and Sequence Prediction Methods for Network Behavior Big Data.

• 2024.01  Datafun, Graph Learning in Dynamic Recommendation Scenarios. [video]

• 2023.12  Bytedance, Intelligent Computing for Complex Graphs.

• 2023.11  The First Academic Forum on Frontiers in Social Group Intelligence, Graph Learning for Nework Behavior Big Data.

• 2023.07  2023 the 4th International Conference on Big Data and Artificial Intelligence (BDAI), Intelligent Computing for Complex Graphs.

• 2023.06  LOGS, Topology Inbalance in Graph Learning. [video]

• 2023.05  Techbeat, Topological Imbalance in Graph Learning. [video]

💻 Service

Area Chair / Senior Program Member:

• ICML 2026
• ICLR 2026
• CIKM 2026

Conference Reviewer:

• NeurIPS 2023/2024/2025

• ICLR 2023/2024/2025

• ICML 2024/2025

• AAAI 2022/2023/2024/2025/2026

• IJCAI 2024/2025/2026

• WWW 2021/2022/2024/2025/2026

• KDD 2021/2022/2024/2025/2026

• ICDM 2023

• CIKM 2024/2025

• DASFFA 2024/2025/2026

• ICASSP 2024/2025

• AISTATS 2025

Journal Reviewer:

• IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)

• IEEE Transactions on Knowledge and Data Engineering (TKDE)

• ACM Transactions on Information Systems (TOIS)

• Artificial Intelligence (AIJ)

• IEEE Transactions on Neural Networks and Learning Systems (TNNLS)

• ACM Transactions on the Web (TWEB)

• IEEE Transactions on Multimedia (TMM)

• IEEE Transactions on Cybernetics (TCYB)

• Pattern Recognition (PR)

• Neural Networks (NN)

• International Journal of Machine Learning and Cybernetics (JMLC)

• Journal of Computer Science and Technology (JCST)

• Journal of Social Computing (JSC)

👩‍🎓 Students

• J. Shi (2025-now, master)

• X. Zhao (2025-now, master)

• J. Li (2025-now, master)

• Z. Zhuang (2025-now, master)

• X. Guan  (2025-now, master)

• J. Luo (2024-now, Ph.D.)

• Z. Guo  (2024-now, master)

• Z. Shen (2024-now, master)

• Z. Wang (2024-now, master)

• W. Xie  (2024-now, master)

• Z. Wang  (2024-now, master)

• T. Gong  (2023-2026, master → Rednote)

• H. Yuan (2022-2026, Ph.D. → Postdoc at Tsinghua University)

• F. Lu   (2022-2026, Ph.D. → Assistant Professor at Zhengzhou University)

• B. Yang (2021-2023, master → Ph.D. at University of Edinburgh)

• Z. Chen (2023-2024, Intern → Ph.D. at University of Edinburgh)

• Y. Gao  (2022-now, Intern → master at HKUST)